JOB SUMMARY:

We are seeking a highly experienced and visionary Senior GCP Data Architect to lead the design, development, and implementation of scalable data solutions in GCP platform. The ideal candidate will possess deep expertise in Google Cloud Platform (GCP), data integration, data migration, system architecture, and Generative AI (GenAI) technologies. This role requires strategic thinking, hands-on technical skills, and the ability to collaborate across cross-functional teams to drive data-driven innovation.

REQUIRED SKILLS & QUALIFICATIONS:

• Bachelor’s or master’s degree in computer science, Information Systems, or related field.
• 15+ years of experience in data architecture, data engineering, or related roles.
• Proven expertise in GCP Data Services (BigQuery, Dataflow, Cloud Data Fusion, Dataproc, Pub/Sub, Cloud Composer, Cloud APIs etc.) and IaC provisioning tool Terraform
• Strong experience with ETL/ELT tools, data integration frameworks, and data migration strategies.
• Deep understanding of system architecture, microservices, and API design.
• Proficiency in SQL, Python, and cloud-native data tools.
• Excellent problem-solving, communication, and stakeholder management skills.

PREFERRED QUALIFICATIONS:

• Certifications in GCP.
• Experience with data security and compliance (e.g., GDPR, HIPAA).
• Hands-on experience with GenAI/ Agentic AI tools, frameworks and platforms (e.g., Vertex AI Agent Builder, Agentspace etc.)
  Job Type: Full-time
  Pay: $140,000.00 - $150,000.00 per year
  Work Location: In perso

• Design and implement robust, scalable, and secure data architectures in GCP environment.
• Lead end-to-end data integration and migration initiatives, ensuring minimal disruption and high data fidelity.
• Define and enforce data governance, data quality, and metadata management standards.
• Collaborate with business stakeholders to understand data requirements and translate them into technical solutions.
• Architect and optimize data pipelines, data lakes, and data warehouses for performance and scalability.
• Provide technical leadership and mentorship to data engineers and other team members.
• Stay current with emerging technologies and industry trends to continuously improve data architecture strategies.